def test_process_windowcalc_s_snps():
infile = (
'chrom\twinstart\twinend\tn_region_ind_snps\tind_id\tpop'
'\ts_star\tnum_s_star_snps\tn_s_star_snps_hap1\tn_s_star_snps_hap2\n'
'363104291\t0\t50000\t179\tmsp_110\tEUR\t85315\t8\t2\t8\n'
'363104291\t0\t50000\t173\tmsp_111\tEUR\t47145\t2\t2\t2\n'
'363104291\t0\t50000\t174\tmsp_112\tASN\t22028\t4\t2\t2\n'
'363104291\t0\t50000\t180\tmsp_113\tEUR\t82882\t12\t7\t4\n'
'363104291\t0\t50000\t184\tmsp_114\tEUR\t111004\t15\t8\t7\n'
'363104291\t0\t50000\t174\tmsp_116\tEUR\t50976\t15\t4\t1\n'
'363104291\t0\t50000\t176\tmsp_117\tASN\t70315\t7\t7\t0\n'
'363104292\t0\t50000\t175\tmsp_118\tEUR\t67973\t3\t0\t3\n'
'363104291\t0\t50000\t171\tmsp_115\tASN\t0\t0\t0\t0\n')
result = Sstar_ECDF.process_windowcalc(StringIO(infile))
# 116 no longer passes as the num is too high
# 111 should also not pass as it matches both (high overlap)
aae(result.columns, [
'start', 'end', 'n_region_ind_snps', 'pop', 's_star', 'haplotype',
'msp_ID'
])
aae(result.start.values, [0, 0, 0])
aae(result.end.values, [50000, 50000, 50000])
aae(result.n_region_ind_snps.values, [179, 176, 175])
aae(result['pop'].values, ['EUR', 'ASN', 'EUR'])
aae(result.s_star.values, [85315, 70315, 67973])
aae(result.haplotype.values, ['msp_110:2', 'msp_117:1', 'msp_118:2'])
aae(result.msp_ID.values,
['msp_110:2_363104291', 'msp_117:1_363104291', 'msp_118:2_363104292'])
def test_filter_by_match():
infile = (
'chrom\twinstart\twinend\tn_region_ind_snps\tind_id\tpop'
'\ts_star\tnum_s_star_snps\tn_s_star_snps_hap1\tn_s_star_snps_hap2\n'
'363104291\t0\t50000\t179\tmsp_110\tEUR\t85315\t10\t2\t8\n'
'363104291\t0\t50000\t173\tmsp_111\tEUR\t47145\t4\t2\t2\n'
'363104291\t0\t50000\t174\tmsp_112\tASN\t22028\t4\t2\t2\n'
'363104291\t0\t50000\t180\tmsp_113\tEUR\t82882\t12\t7\t4\n'
'363104291\t0\t50000\t184\tmsp_114\tEUR\t111004\t15\t8\t7\n'
'363104291\t0\t50000\t174\tmsp_116\tEUR\t50976\t5\t4\t1\n'
'363104291\t0\t50000\t176\tmsp_117\tASN\t70315\t7\t7\t0\n'
'363104292\t0\t50000\t175\tmsp_118\tEUR\t67973\t3\t0\t3\n'
'363104291\t0\t50000\t171\tmsp_115\tASN\t0\t0\t0\t0\n')
window = Sstar_ECDF.process_windowcalc(StringIO(infile), 0.5)
match_file = (
'chr\tstart\tend\tisc\thaplotype\tpopulation'
'\tmatch_pct\tpvalue\tmatching_windows\n'
'363104291\t0\t50000\t199\tmsp_110:1\tEUR\t0.8\t0.01\t2217\n'
'363104291\t0\t50000\t199\tmsp_110:2\tEUR\t0.8\t0.02\t2217\n')
result = Sstar_ECDF.filter_by_match(window, StringIO(match_file), 0.02)
afe(
result,
pd.DataFrame({
'start': [0],
'end': [50000],
'n_region_ind_snps': [179],
'pop': ['EUR'],
's_star': [85315],
'msp_ID': ['msp_110:2_363104291'],
}))
# result empty as pvalue too low
result = Sstar_ECDF.filter_by_match(window, StringIO(match_file), 0.01)
afe(result,
pd.DataFrame({
'start': [],
'end': [],
'n_region_ind_snps': [],
'pop': [],
's_star': [],
'msp_ID': [],
}),
check_index_type=False,
check_dtype=False)
def test_get_chromosomes(mocker):
data = StringIO('1063938750\n' '1222356006\n' '1634154403\n')
mock_file = mocker.patch('Sstar_ECDF.open', return_value=data)
result = [e for e in Sstar_ECDF.get_chromosomes('mock')]
mock_file.assert_called_once_with('mock', 'r')
assert result == ['1063938750', '1222356006', '1634154403']
mock_file.reset_mock()
data = StringIO('')
mock_file = mocker.patch('Sstar_ECDF.open', return_value=data)
assert [e for e in Sstar_ECDF.get_chromosomes('mock_empty')] == []
mock_file.assert_called_once_with('mock_empty', 'r')
def test_null_db_combine(null_db):
infile = StringIO(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'1 0 50000 333 4 161 msp_110 EUR 25211\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_111 EUR 25211\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_112 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_113 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_114 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_115 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_116 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_116 ASN 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_116 EUR 0\n'.replace(' ', '\t') + # skip
'')
null_db.read_windowcalc(infile)
print(null_db.DB)
print(null_db.DB.index)
index = pd.MultiIndex.from_tuples(
[
('ASN', 162, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
],
names=['pop', 'n_region_ind_snps', 's_star'])
ase(null_db.DB, pd.Series([1, 1, 1, 5], index=index))
infile = StringIO(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'1 0 50000 333 4 161 msp_110 EUR 25211\n'.replace(' ', '\t') +
'1 0 50000 333 4 162 msp_111 EUR 25211\n'.replace(' ', '\t') + '')
null_db2 = Sstar_ECDF.Null_DB()
null_db2.read_windowcalc(infile)
index = pd.MultiIndex.from_tuples(
[
('EUR', 161, 25211),
('EUR', 162, 25211),
],
names=['pop', 'n_region_ind_snps', 's_star'])
ase(null_db2.DB, pd.Series([1, 1], index=index))
null_db.combine(null_db2)
index = pd.MultiIndex.from_tuples(
[
('ASN', 162, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
],
names=['pop', 'n_region_ind_snps', 's_star'])
ase(null_db.DB, pd.Series([1, 2, 2, 5], index=index))
def test_region_files():
result = [c for c in Sstar_ECDF.region_files('base', 'a b c'.split())]
assert result == [
os.path.join('base', 'a.windowcalc.gz'),
os.path.join('base', 'b.windowcalc.gz'),
os.path.join('base', 'c.windowcalc.gz'),
]
result = [
c for c in Sstar_ECDF.region_files('', '1 2 3'.split(), '{chrom}.txt')
]
assert result == [
'1.txt',
'2.txt',
'3.txt',
]
result = [c for c in Sstar_ECDF.region_files('base', [])]
assert result == []
def null_db():
return Sstar_ECDF.Null_DB()
def test_filter_by_sstar():
df = pd.DataFrame({
'start': [0, 0, 0],
'end': [50000, 50000, 50000],
'n_region_ind_snps': [179, 179, 178],
'pop': ['EUR', 'EUR', 'EUR'],
's_star': [85315, 85314, 85313],
'msp_ID':
['msp_110:2_363104292', 'msp_110:2_363104293', 'msp_110:2_363104291'],
})
null_db = Sstar_ECDF.Null_DB()
index = pd.MultiIndex.from_tuples(
[
('EUR', 179, 25211),
('EUR', 179, 85313),
('EUR', 179, 85314),
('EUR', 179, 85315),
('EUR', 179, 85316),
('EUR', 178, 25211),
],
names=['pop', 'n_region_ind_snps', 's_star'])
null_db.DB = pd.Series([2, 2, 2, 2, 2, 2], index=index)
# nothing
result = Sstar_ECDF.filter_by_sstar(df, null_db, -1)
afe(result,
pd.DataFrame({
'start': [],
'end': [],
'msp_ID': []
}),
check_like=True,
check_dtype=False)
# last
result = Sstar_ECDF.filter_by_sstar(df, null_db, 0)
afe(result,
pd.DataFrame({
'start': [0],
'end': [50000],
'msp_ID': ['msp_110:2_363104291']
}),
check_like=True,
check_dtype=False)
result = Sstar_ECDF.filter_by_sstar(df, null_db, 0.2)
afe(result,
pd.DataFrame({
'start': [0, 0],
'end': [50000, 50000],
'msp_ID': ['msp_110:2_363104291', 'msp_110:2_363104292']
}),
check_like=True,
check_dtype=False)
# Note, groupby sorts by pop, then n_region
result = Sstar_ECDF.filter_by_sstar(df, null_db, 0.4)
afe(result,
pd.DataFrame({
'start': [0, 0, 0],
'end': [50000, 50000, 50000],
'msp_ID': [
'msp_110:2_363104291', 'msp_110:2_363104292',
'msp_110:2_363104293'
]
}),
check_like=True,
check_dtype=False)
# empty window input
df = pd.DataFrame({
'start': [],
'end': [],
'n_region_ind_snps': [],
'pop': [],
's_star': [],
'msp_ID': [],
})
result = Sstar_ECDF.filter_by_sstar(df, null_db, 0.05)
afe(result,
pd.DataFrame({
'start': [],
'end': [],
'msp_ID': []
}),
check_like=True,
check_dtype=False)
def test_main_generate_bed():
runner = CliRunner()
with runner.isolated_filesystem():
# build up null db
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
('EUR', 164, 25213),
('EUR', 164, 25214),
('EUR', 164, 25215),
],
names=['pop', 'n_region_ind_snps', 's_star'])
dat = list(range(12))
null_db = Sstar_ECDF.Null_DB()
null_db.DB = pd.Series(dat, index=index)
null_db.save('null.pkl')
# build up admixed window calc files
with gzip.open('1.windowcalc.gz', 'wt') as window:
window.write(
'chrom\twinstart\twinend\tn_region_ind_snps\tind_id\tpop'
'\ts_star\tnum_s_star_snps\tn_s_star_snps_hap1\tn_s_star_snps_hap2\n'
'1\t0\t50000\t179\tmsp_110\tEUR\t85315\t10\t2\t8\n')
with gzip.open('2.windowcalc.gz', 'wt') as window:
window.write(
'chrom\twinstart\twinend\tn_region_ind_snps\tind_id\tpop'
'\ts_star\tnum_s_star_snps\tn_s_star_snps_hap1\tn_s_star_snps_hap2\n'
'2\t0\t50000\t179\tmsp_110\tEUR\t85315\t10\t2\t8\n')
# build tsv files
with gzip.open('1.tsv.gz', 'wt') as tsv:
tsv.write('chr\tstart\tend\tisc\thaplotype\tpopulation'
'\tmatch_pct\tpvalue\tmatching_windows\n'
'1\t0\t50000\t199\tmsp_110:1\tEUR\t0.8\t0.03\t2217\n'
'1\t0\t50000\t199\tmsp_110:2\tEUR\t0.8\t0.01\t2217\n')
with gzip.open('2.tsv.gz', 'wt') as tsv:
tsv.write('chr\tstart\tend\tisc\thaplotype\tpopulation'
'\tmatch_pct\tpvalue\tmatching_windows\n'
'2\t0\t50000\t199\tmsp_110:1\tEUR\t0.8\t0.01\t2217\n')
# chrom list
with open('chroms.txt', 'w') as chrom:
chrom.write('1\n2\n')
# run main
result = runner.invoke(
Sstar_ECDF.main, 'generate-bed '
'--chr-list chroms.txt '
'--outfile {chrom}.test.bed '
'--null-db null.pkl ')
assert result.exit_code == 0
# check output files
out1 = open('1.test.bed').readlines()
assert out1 == ['msp_ID\tstart\tend\n', 'msp_110:2_1\t0\t50000\n']
out2 = open('2.test.bed').readlines()
assert out2 == ['msp_ID\tstart\tend\n']
def test_main_build_null_db():
runner = CliRunner()
with runner.isolated_filesystem():
# build chromosome file
with open('chroms.txt', 'w') as output:
output.write('10\n' '12\n' '16\n')
# make fake window files
with gzip.open('10.windowcalc.gz', 'wt') as output:
output.write(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'2 0 50000 333 4 161 msp_110 EUR 25211\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_111 EUR 25211\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_112 EUR 25212\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_113 EUR 25212\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_114 EUR 25212\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_115 EUR 25212\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_116 EUR 25212\n'.replace(' ', '\t') +
'2 0 50000 333 4 162 msp_116 ASN 25212\n'.replace(' ', '\t') +
'')
with gzip.open('12.windowcalc.gz', 'wt') as output:
output.write(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'3 0 50000 333 4 161 msp_110 ASN 25211\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_111 EUR 25211\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_112 ASN 25212\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_113 EUR 25212\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_114 ASN 25212\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_115 EUR 25212\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_116 EUR 25212\n'.replace(' ', '\t') +
'3 0 50000 333 4 162 msp_116 ASN 25212\n'.replace(' ', '\t') +
'')
with gzip.open('16.windowcalc.gz', 'wt') as output:
output.write(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'1 0 50000 333 4 164 msp_110 EUR 25211\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_111 ASN 25211\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_112 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_113 ASN 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_114 ASN 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_115 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_116 EUR 25212\n'.replace(' ', '\t') +
'1 0 50000 333 4 164 msp_116 ASN 25212\n'.replace(' ', '\t') +
'')
with gzip.open('18.windowcalc.gz', 'wt') as output:
output.write(
'chrom\twinstart\twinend\tn_snps\tn_ind_snps\t'
'n_region_ind_snps\tind_id\tpop\ts_star\n' +
'1 0 50000 333 4 161 msp_110 EUR 25211\n'.replace(' ', '\t') +
'NOT READ\n'
'1 0 50000 333 4 162 msp_116 ASN 25212\n'.replace(' ', '\t') +
'')
# build db
result = runner.invoke(
Sstar_ECDF.main, ' build-null-db '
'--chr-list chroms.txt '
'--outfile test.pkl')
assert result.exit_code == 0
# check db
assert os.path.exists('test.pkl')
db = Sstar_ECDF.Null_DB()
db.load('test.pkl')
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
],
names=['pop', 'n_region_ind_snps', 's_star'])
ase(db.DB, pd.Series([1, 4, 1, 3, 1, 2, 8, 1, 3], index=index))
def test_main_combine_null_dbs():
runner = CliRunner()
with runner.isolated_filesystem():
# build up null dbs
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
('EUR', 164, 25213),
('EUR', 164, 25214),
('EUR', 164, 25215),
],
names=['pop', 'n_region_ind_snps', 's_star'])
dat = list(range(12))
null_db = Sstar_ECDF.Null_DB()
null_db.DB = pd.Series(dat, index=index)
null_db.save('null.pkl')
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
('EUR', 164, 25213),
('EUR', 164, 25214),
('EUR', 164, 25215),
],
names=['pop', 'n_region_ind_snps', 's_star'])
dat = list(range(0, 24, 2))
null_db = Sstar_ECDF.Null_DB()
null_db.DB = pd.Series(dat, index=index)
null_db.save('null2.pkl')
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
('EUR', 164, 25213),
('EUR', 164, 25214),
('EUR', 164, 25215),
],
names=['pop', 'n_region_ind_snps', 's_star'])
dat = list(range(0, 36, 3))
null_db = Sstar_ECDF.Null_DB()
null_db.DB = pd.Series(dat, index=index)
null_db.save('null3.pkl')
# run main
result = runner.invoke(
Sstar_ECDF.main, 'combine-null-dbs '
'--outfile test.pkl '
'null.pkl null2.pkl null3.pkl')
assert result.exit_code == 0
# check output files
db = Sstar_ECDF.Null_DB()
db.load('test.pkl')
index = pd.MultiIndex.from_tuples(
[
('ASN', 161, 25211),
('ASN', 162, 25212),
('ASN', 164, 25211),
('ASN', 164, 25212),
('EUR', 161, 25211),
('EUR', 162, 25211),
('EUR', 162, 25212),
('EUR', 164, 25211),
('EUR', 164, 25212),
('EUR', 164, 25213),
('EUR', 164, 25214),
('EUR', 164, 25215),
],
names=['pop', 'n_region_ind_snps', 's_star'])
ase(db.DB, pd.Series(range(0, 72, 6), index=index))